Comments on: Understanding Natural Language Processing For Social Media Monitoring

By: Tan_yong_tai

Tan_yong_tai — Sat, 26 Feb 2011 23:16:32 +0000

Interesting. Thank you.

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Ford KA Parts — Tue, 01 Jun 2010 00:16:54 +0000

Because they can train the tool to understand the dynamics of conversations around a particular client and build upon that learning in an ongoing fashion, they can produce accuracies in the low- to mid-80s over time and are even around 83% on some clients now.

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Ford KA Parts — Mon, 31 May 2010 17:16:54 +0000

By: Why You Shouldnâ€™t Trust Automated Sentiment Scoring | BrettMBell.com

Why You Shouldnâ€™t Trust Automated Sentiment Scoring | BrettMBell.com — Sat, 08 May 2010 03:13:47 +0000

[...] few months ago, we discussed automated sentiment scoring with Jeffrey Caitlin, CEO of Lexalytics, a leading natural language processing firm that serves as the engine behind [...]

By: Why You Shouldn't Trust Automated Sentiment Scoring

Why You Shouldn't Trust Automated Sentiment Scoring — Mon, 26 Apr 2010 10:26:18 +0000

[...] few months ago, we discussed automated sentiment scoring with Jeffrey Caitlin, CEO of Lexalytics, a leading natural language processing firm that serves as the engine behind [...]

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By: JasonFalls

JasonFalls — Sat, 05 Dec 2009 01:38:43 +0000

You're welcome. Thanks for the comment!

By: jtorras

jtorras — Fri, 04 Dec 2009 11:56:56 +0000

Thanks for this article Jason!
At Inbenta we are using our “semantic clustering” technology to group conversations that have a similar topic. As you told, they are not necessarily good or bad, but it's interesting to see patterns related to semantic meaning of those conversations